A Company Wants to Predict the Sale Prices of Houses

question 9

Multiple Choice

A company wants to predict the sale prices of houses based on available historical sales data. The target variable in the company's dataset is the sale price. The features include parameters such as the lot size, living area measurements, non-living area measurements, number of bedrooms, number of bathrooms, year built, and postal code. The company wants to use multi-variable linear regression to predict house sale prices. Which step should a machine learning specialist take to remove features that are irrelevant for the analysis and reduce the model's complexity?

• A) Plot a histogram of the features and compute their standard deviation. Remove features with high variance.
• B) Plot a histogram of the features and compute their standard deviation. Remove features with low variance.
• C) Build a heatmap showing the correlation of the dataset against itself. Remove features with low mutual correlation scores.
• D) Run a correlation check of all features against the target variable. Remove features with low target variable correlation scores.

---

Definitions:

Changing Characteristics

The process or act of altering features, qualities, or attributes of something, often implying evolution or improvement.

Find Button

A feature in software that allows users to search for specific text, files, or information quickly.

HOME Tab

The primary or default tab in many software applications, offering access to the main functions and settings.

Filter By Query

A feature that allows users to refine search results or dataset visibility based on specified criteria or commands.